Robot Vision Positioning for Interaction Machine Alignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Manual training of robot devices to determine interaction machine positions is labor-intensive and requires repeated effort when the robot device needs to interact with multiple machines, as the position of the robot device relative to the machine changes.
Innovation Solution
A robot device equipped with an optical detection system and a control device that uses reference markings and machine learning methods, including neural networks, to detect and determine the interaction machine position indirectly, allowing for automatic adaptation to new positions without the need for repeated training.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual training is used to teach the robot device the exact interaction machine position, then the robot device can accurately interact with the machine, but the manual human effort and time required increases significantly
Solution Approach 1:
A reference marking is introduced as an intermediary element attached to the interaction machine. The optical detection device detects this reference marking to indirectly determine the interaction machine position, rather than requiring manual teaching of the position. This intermediary marker enables automatic position detection while maintaining accuracy.
Solution Approach 2:
The manual mechanical training process is replaced by an optical detection system. Instead of manually moving the robot to teach positions, an optical detection device with cameras detects the reference marking and automatically calculates the interaction machine position through coordinate transformation, eliminating the need for manual intervention.
2Adaptability or versatility
If manual training is repeated for each machine interaction, then the robot device can adapt to different machines, but the cumulative manual effort and time required increases
Solution Approach 1:
The reference marking serves as a universal identifier that can be attached to any interaction machine. The same optical detection device and detection algorithm can be used across multiple machines, providing a multi-functional solution that eliminates the need for machine-specific manual training procedures.
Solution Approach 2:
The reference marking is pre-attached to the interaction machine before the robot device arrives. This preliminary preparation enables the robot to immediately detect and adapt to the machine position without requiring time-consuming manual training, allowing quick deployment to different machines.
3Adaptability or versatility
If the robot device position changes relative to the machine, then the robot can perform different tasks, but retraining is required which increases manual effort
Solution Approach 1:
The system dynamically adapts to changes in robot device position by detecting the reference marking from different viewpoints. The control device performs coordinate transformation based on the detected marker position, automatically adjusting the interaction machine position calculation without requiring retraining, enabling flexible task performance.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient and accurate detection of interaction machine positions, reducing manual effort and errors, and allowing the robot device to perform interactions such as object transfer and positioning without requiring retraining when machine positions change.
Implementation Method 1
The robot device is configured to detect a surrounding area image of an area surrounding the robot device by means of an optical detection device. The optical detection device may have, for example, cameras which can be configured to photograph the surrounding area image in the visible light spectrum
Data Source
AI summary
A robot device includes an optical detection device configured to detect a surrounding area image of an area surrounding the robot device. The robot device further includes a control device storing a predetermined reference marking and a predetermined reference position of the reference marking. The control device is configured to detect an image detail that shows the reference marking of the interaction machine in the surrounding area image of the area surrounding the robot device, detect the predetermined reference marking in the image detail, determine a distortion of the predetermined reference marking in the image detail, determine a spatial position of the reference marking, determine an interaction machine position of at least one element of the interaction machine with respect to the robot device from the spatial position of the reference marking, and subject the robot device to closed-loop control and/or open-loop control.